Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model

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A Survey on Multi-Task Learning (2017, background): “regression problems, where each output is treated as a task and all the tasks share the training data, are investigated in [92], [94], [95], [96] to not only learn the relations among different outputs/tasks”
Multi-Task CNN Model for Attribute Prediction (2015, methodology): “While Max-margin is known by its discriminative power, Bayesian is more flexible and thus better suited to engage any a priori or performance inference [31].”
On Multiplicative Multitask Feature Learning (2014, background): “, 2008), or by examining the tasks’ covariance matrix (Bonilla et al., 2007; Zhang and Yeung, 2010; Guo et al., 2011; Yang et al., 2013).”
Multi-task Sparse Structure Learning with Gaussian Copula Models (2016, background): “Related Work MTL has attracted a great deal of attention in the past few years and consequently many algorithms have been proposed (Evgeniou and Pontil, 2004; Argyriou et al., 2007; Xue et al., 2007; Jacob et al., 2008; Obozinski et al., 2010; Zhou et al., 2011b; Zhang and Yeung, 2010; Yang et al., ”